• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1255-1262
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• 2012

Look into the nuclear power plant of Wolsong currently, it is controlled in order to required operating pressure with PI controller. PI controller has a simple structure and satisfy design requirements to gain setting. However, It is difficult to control without changing the gain from produce changes in parameters such as loss of the valves and the pipes. To solve these problems, the dynamic change of the PI controller gain, or to compensate for the PI controller output is desirable to configure the controller. The aim of this research and development in the parameter variations can be controlled to a stable controller design which is reduced an error and a vibration. Proposed PI/NN control techniques is the PI controller and the neural network controller that combines a parallel and the neural network controller part is compensated output of the controller for changes in the parameters were designed to be robust. To directly evaluate the controller performance can be difficult to test in real processes to reflect the characteristics of the process. Therefore, we develope the simulator model using the real process data and simulation results when compared with the simulated process characteristics that showed changes in the parameters. As a result the PI/NN controller error and was confirmed to reduce vibrations.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.35-41
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• 2016

Internet of Things (IoT) services are widely used in appliances of daily life and industries. IoT services also provide various conveniences to users and are expected to affect value added of all industries and national competitiveness. However, a variety of security threats are increased in IoT environments and lowers reliability of IoT devices and services that make some obstacles for commercialization. The attacks arising in IoT environments are making industrial and normal life accidents unlike existing information leak and monetary damages, and can expand damage scale of leakage of personal information and privacy more than existing them. To solve these problems, we design a session key based access control scheme for secure communications in IoT environments. The proposed scheme reinforces message security by generating session key between device and access control network system. We analyzed the stability of the proposed access scheme in terms of data forgery and corruption, unauthorized access, information disclosure, privacy violations, and denial of service attacks. And we also evaluated the proposed scheme in terms of permission settings, privacy indemnity, data confidentiality and integrity, authentication, and access control.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.803-804
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• 2016

With the advent of Germany's Industry 4.0, research of smart factory to applying the ICT in manufacturing industries is in progress. But the current system controlled equipment using the data declared in the embedded systems. In this paper, we proposed equipment control method to implement smart factory based on IoT. This method is create D/B table of data declared in equipment. and equipment shall call all of control unit parameters. When using the present method, it is possible to efficiently control the number of equipment as less network resource. Also It can operating a factory efficiently.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.41-49
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• 2022

The Internet Engineering Task Force (IETF) has standardized RPL (IPv6 Routing Protocol for Low-power Lossy Network) as a routing protocol for Low Power and Lossy Networks (LLNs), a low power loss network environment. RPL creates a route through an Objective Function (OF) suitable for the service required by LLNs and builds a Destination Oriented Directed Acyclic Graph (DODAG). Existing studies check the residual energy of each node and select a parent with the highest residual energy to build a DODAG, but the energy exhaustion of the parent can not avoid the network disconnection of the children nodes. Therefore, this paper proposes EC-RPL (Enhanced Connectivity-RPL), in which ta node leaves DODAG in advance when the remaining energy of the node falls below the specified energy threshold. The proposed protocol is implemented in Contiki, an open-source IoT operating system, and its performance is evaluated in Cooja simulator, and the number of control messages is compared using Foren6. Experimental results show that EC-RPL has 6.9% lower latency and 5.8% fewer control messages than the existing RPL, and the packet delivery rate is 1.7% higher.

• Journal of Korean Association for Spatial Structures
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• v.20 no.2
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• pp.51-58
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• 2020

Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.552-555
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• 2001

In this paper, an intelligent demand control system was introduced. This system are composed of demand controller, RTU, power line modem and HMI program. The proposed demand controller was capable of synchronizing with watt-hour meter recommended by KEPCO(Korea Electrical Power Corporation). To control remote loads, network function using powerline communication is implemented in RTU with HMI program and novices are able to operate system easily. Additionally using the power line, the cost and time of installation can b saved. The system performance was proved with a several experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1389-1393
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• 2011

In this paper, we implement the VLC system based on CAN communication which is usually used in car, plane, ship, product line control system, medical device and industrial device. We implement the application circuit which is VLC and CAN communication and explain the principle. Circuit's pulse features are demonstrated by each part's signal. Total communication distance is 3m and it's transmission performance is error free.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.43-48
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• 1992

The automation system oriented as one of the second year automation projects for the small and medium sized enterprises(SME) was developed for the improvement of the production rate and cut the required manpower in the field of the relay which is one of the small electric components used in various industrial fields. The objectives of this study are not only improving the international competition of the relay itself but also partially solving the technical and financial problems featured by common bottlenecks of the SME for efficient assembly automation. For the purpose of these objectives, several topics are studied as followings. - Analyzing the adjustment process and determining the specification of the automation system. - Determining the layout for the automation system to meet the determined specification. - Detail design of the automation system for relay adjustment and inspection. - Control system design - Automation system development and performance test.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.398-398
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• 2000

Since there is a blind zone in driver's view around the excavator, industrial accidents between the equipment and the workers within the zone have been occurred frequently. The purpose of this paper is to develop a obstacle recognition system which can prevent such an accident by providing the driver with the information on direction and distance of the obstacle within the blind zone. We designed the ultrasonic sensor based obstacle recognition system which consists of sensor arrays and a control unit connected via CAN(controller area network). The Cross-correlation technique and histogramic probability distribution method are used as a reliable obstacle detection algorithms to remove the environmental noise. The experimental results using a real excavator show the effectiveness of the system.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.311-315
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• 2006

"Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin